Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Katie Borland"'
Development and assessment of a machine learning tool for predicting emergency admission in Scotland
Autor:
James Liley, Gergo Bohner, Samuel R. Emerson, Bilal A. Mateen, Katie Borland, David Carr, Scott Heald, Samuel D. Oduro, Jill Ireland, Keith Moffat, Rachel Porteous, Stephen Riddell, Simon Rogers, Ioanna Thoma, Nathan Cunningham, Chris Holmes, Katrina Payne, Sebastian J. Vollmer, Catalina A. Vallejos, Louis J. M. Aslett
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-13 (2024)
Abstract Emergency admissions (EA), where a patient requires urgent in-hospital care, are a major challenge for healthcare systems. The development of risk prediction models can partly alleviate this problem by supporting primary care interventions a
Externí odkaz:
https://doaj.org/article/87b768a0942545ce93fa1cd0c65c73ab
Autor:
James Liley, Gergo Bohner, Samuel R. Emerson, Bilal A. Mateen, Katie Borland, David Carr, Scott Heald, Samuel D. Oduro, Jill Ireland, Keith Moffat, Rachel Porteous, Stephen Riddell, Simon Rogers, Ioanna Thoma, Nathan Cunningham, Chris Holmes, Katrina Payne, Sebastian J. Vollmer, Catalina A. Vallejos, Louis J. M. Aslett
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/0c2c5f44ee024c08b8eaf5ef02d7bcc0
Development and assessment of a machine learning tool for predicting emergency admission in Scotland
Autor:
Stephen Riddell, Bilal A. Mateen, Catalina A. Vallejos, Christopher Holmes, Katrina Payne, Gergo Bohner, Katie Borland, Keith Ra. Moffat, Nathan Cunningham, Sebastian J. Vollmer, David Carr, James Liley, Samuel D. Oduro, Louis J. M. Aslett, Jill Ireland, Samuel R. Emerson, Rachel Porteous, Scott Heald
Avoiding emergency hospital admission (EA) is advantageous to individual health and the healthcare system. We develop a statistical model estimating risk of EA for most of the Scottish population (> 4.8Mindividuals) using electronic health records, s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afa0e9cdd18eca6b6e66829a866fecf8
https://doi.org/10.1101/2021.08.06.21261593
https://doi.org/10.1101/2021.08.06.21261593
